Global summary

Identifying changes in the reproduction number, rate of spread, and doubling time during the course of the COVID-19 outbreak whilst accounting for potential biases due to delays in case reporting both nationally and subnationally. These results are impacted by changes in testing effort, increases and decreases in testing effort will increase and decrease reproduction number estimates respectively (see Methods for further explanation).

Using data available up to the: 2020-04-25

Note that it takes time for infection to cause symptoms, to get tested for SARS-CoV-2 infection, for a positive test to return and ultimately to enter the case data presented here. In other words, today’s case data are only informative of new infections about two weeks ago. This is reflected in the plots below, which are by date of infection.

Expected daily confirmed cases by country


Figure 1: The results of the latest reproduction number estimates (based on estimated confirmed cases with a date of infection on the 2020-04-16) can be summarised by whether confirmed cases are likely increasing or decreasing. This represents the strength of the evidence that the reproduction number in each region is greater than or less than 1, respectively (see the methods for details). Countries with fewer than 60 confirmed cases reported on a single day are not included in the analysis (light grey) as there is not enough data to reliably estimate the reproduction number.

Summary of latest reproduction number and confirmed case count estimates by date of infection


Figure 1: Confirmed cases with date of infection on the 2020-04-16 and the time-varying estimate of the effective reproduction number (light bar = 90% credible interval; dark bar = the 50% credible interval.). Regions are ordered by the number of expected daily confirmed cases and shaded based on the expected change in daily confirmed cases. The horizontal dotted line indicates the target value of 1 for the effective reproduction no. required for control and a single case required for elimination. The vertical dashed line indicates the date of report generation.

Reproduction numbers over time in the six regions expected to have the most new confirmed cases


Figure 2: Time-varying estimate of the effective reproduction number (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in the regions expected to have the highest number of new confirmed cases. Estimates are shown up to the 2020-04-16 from when forecasts are shown. These should be considered indicative only. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The horizontal dotted line indicates the target value of 1 for the effective reproduction no. required for control. The vertical dashed line indicates the date of report generation.

Reported confirmed cases and their estimated date of infection in the six regions expected to have the most new confirmed cases


Figure 3: Confirmed cases by date of report (bars) and their estimated date of infection (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in the regions expected to have the highest number of new confirmed cases. Estimates are shown up to the 2020-04-16 from when forecasts are shown. These should be considered indicative only. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The vertical dashed line indicates the date of report generation.

Reproduction numbers over time in all regions


Figure 4: Time-varying estimate of the effective reproduction number (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in all regions. Estimates are shown up to the 2020-04-16 from when forecasts are shown. These should be considered indicative only. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The horizontal dotted line indicates the target value of 1 for the effective reproduction no. required for control. The vertical dashed line indicates the date of report generation.

Reported confirmed cases and their estimated date of infection in all regions

Figure 5: Confirmed cases by date of report (bars) and their estimated date of infection (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in all regions. Estimates are shown up to the 2020-04-16 from when forecasts are shown. These should be considered indicative only. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The vertical dashed line indicates the date of report generation.

Latest estimates (as of the 2020-04-16)

Table 1: Latest estimates (as of the 2020-04-16) of the number of confirmed cases by date of infection, the effective reproduction number, and the doubling time (when negative this corresponds to the halving time) in each region. The mean and 90% credible interval is shown.
Country/Region New confirmed cases by infection date Expected change in daily cases Effective reproduction no. Doubling time (days)
Afghanistan 103 (54 – 295) Increasing 1.3 (1.1 – 2.1) 15 (6.1 – -19)
Algeria 107 (77 – 168) Unsure 1 (0.8 – 1.2) -69 (13 – -9.8)
Argentina 125 (83 – 176) Likely increasing 1.1 (0.9 – 1.2) 41 (10 – -25)
Armenia 85 (55 – 132) Likely increasing 1.3 (1 – 1.7) 12 (5 – -28)
Australia 26 (6 – 59) Unsure 0.8 (0.3 – 1.2) -8.1 (6.8 – -2.5)
Austria 74 (47 – 129) Unsure 1 (0.6 – 1.3) -23 (12 – -6.8)
Azerbaijan 40 (18 – 80) Unsure 1.1 (0.6 – 1.4) 210 (7.5 – -6.2)
Bahrain 160 (99 – 202) Increasing 1.4 (1.1 – 1.8) 8.5 (5.5 – 23)
Bangladesh 458 (421 – 550) Increasing 1.2 (1.1 – 1.4) 16 (10 – 44)
Belarus 692 (621 – 797) Increasing 1.2 (1.1 – 1.3) 15 (11 – 29)
Belgium 1133 (955 – 1262) Likely decreasing 0.9 (0.8 – 1) -45 (280 – -21)
Bolivia 55 (33 – 87) Increasing 1.3 (1 – 1.7) 14 (5.5 – -24)
Bosnia and Herzegovina 44 (15 – 100) Unsure 1.1 (0.3 – 1.9) 120 (4.9 – -4.8)
Brazil 3144 (2909 – 3447) Increasing 1.1 (1.1 – 1.2) 33 (19 – 150)
Bulgaria 83 (55 – 114) Increasing 1.4 (1.1 – 1.8) 9.4 (4.2 – -64)
Cameroon 111 (77 – 140) Increasing 1.7 (1.4 – 2) 6.2 (3.8 – 19)
Canada 1834 (1672 – 2020) Increasing 1.1 (1 – 1.2) 50 (24 – 600)
Chile 487 (401 – 637) Likely increasing 1.1 (1 – 1.2) 58 (15 – -36)
China 17 (3 – 34) Decreasing 0.5 (0.1 – 0.8) -3.3 (-9.9 – -1.8)
Colombia 241 (177 – 324) Increasing 1.2 (1 – 1.3) 18 (7.8 – -69)
Cote dIvoire 65 (37 – 100) Likely increasing 1.3 (0.9 – 1.6) 24 (4.7 – -9.4)
Croatia 54 (29 – 102) Unsure 1.2 (0.7 – 1.6) 16 (4.7 – -11)
Cuba 63 (37 – 95) Unsure 1.1 (0.9 – 1.4) 40 (7 – -9.3)
Czechia 98 (61 – 146) Unsure 0.9 (0.6 – 1.2) -41 (11 – -6.9)
Denmark 151 (112 – 194) Unsure 1 (0.7 – 1.2) -63 (15 – -10)
Djibouti 37 (12 – 72) Likely decreasing 0.7 (0.2 – 1) -5.9 (-90 – -3)
Dominican Republic 204 (161 – 232) Likely decreasing 0.9 (0.8 – 1) -41 (39 – -13)
Ecuador 390 (346 – 460) Unsure 1 (0.9 – 1.2) 31 (12 – -65)
Egypt 213 (189 – 251) Likely increasing 1.1 (1 – 1.3) 21 (11 – -170)
Equatorial Guinea 37 (17 – 58) Increasing 2 (1.3 – 2.6) 4.5 (2.4 – 20)
Estonia 39 (17 – 92) Unsure 1.3 (0.6 – 2) 40 (4.1 – -5)
Finland 140 (90 – 225) Unsure 1.1 (0.9 – 1.3) 59 (10 – -14)
France 1992 (1798 – 2216) Likely decreasing 1 (0.9 – 1) -140 (43 – -29)
Germany 2208 (2070 – 2290) Decreasing 0.9 (0.9 – 1) -29 (-69 – -19)
Ghana 71 (31 – 104) Unsure 1 (0.7 – 1.3) 290 (9.4 – -9.7)
Greece 65 (36 – 109) Increasing 1.5 (1.2 – 2) 5.5 (3.2 – 19)
Guinea 90 (52 – 144) Increasing 1.5 (1.1 – 1.9) 11 (4.7 – -22)
Honduras 25 (6 – 35) Increasing 1.5 (0.9 – 2.6) 10 (3 – -9.3)
Hungary 119 (69 – 189) Likely increasing 1.2 (0.8 – 1.6) 21 (7.4 – -22)
Iceland 16 (1 – 41) Unsure 1.2 (0.4 – 2.2) 37 (2.6 – -2.9)
India 1472 (1391 – 1608) Increasing 1.1 (1.1 – 1.2) 27 (18 – 65)
Indonesia 372 (286 – 517) Likely increasing 1.1 (0.9 – 1.2) 110 (15 – -23)
Iran 1167 (1011 – 1308) Decreasing 0.9 (0.8 – 1) -27 (-87 – -16)
Iraq 60 (36 – 100) Likely increasing 1.3 (0.9 – 2) 11 (3.3 – -9.7)
Ireland 649 (563 – 779) Unsure 1 (0.9 – 1.1) -94 (32 – -21)
Israel 360 (267 – 525) Unsure 1.1 (0.9 – 1.4) 34 (11 – -32)
Italy 2931 (2781 – 3066) Likely decreasing 1 (0.9 – 1) -88 (990 – -41)
Japan 458 (402 – 530) Likely decreasing 0.9 (0.9 – 1.1) -41 (86 – -18)
Kazakhstan 136 (89 – 193) Likely increasing 1.1 (1 – 1.3) 38 (9.5 – -22)
Kosovo 48 (25 – 85) Unsure 1.4 (0.8 – 2.1) 12 (3.6 – -11)
Kuwait 186 (153 – 230) Increasing 1.3 (1.1 – 1.6) 13 (6.8 – 110)
Kyrgyzstan 28 (4 – 59) Unsure 1.1 (0.6 – 1.8) 56 (4.3 – -4.6)
Latvia 44 (11 – 134) Likely increasing 2 (0.7 – 4.5) 7 (1.7 – -6.8)
Lebanon 74 (9 – 312) Likely increasing 3.9 (0.6 – 6.5) 1.9 (1.1 – -2.8)
Lithuania 39 (22 – 64) Unsure 1 (0.5 – 1.4) -61 (7.2 – -5.2)
Luxembourg 36 (11 – 67) Unsure 1 (0.7 – 1.4) -52 (7.8 – -7.2)
Malaysia 71 (50 – 141) Unsure 1 (0.6 – 1.6) -110 (10 – -8.6)
Mexico 994 (885 – 1092) Increasing 1.3 (1.1 – 1.5) 12 (9.2 – 19)
Moldova 138 (92 – 201) Unsure 1.1 (0.9 – 1.4) 28 (8.8 – -19)
Morocco 202 (148 – 305) Unsure 1.1 (0.9 – 1.3) 93 (12 – -16)
Netherlands 778 (708 – 839) Decreasing 0.9 (0.8 – 0.9) -25 (-60 – -15)
New Zealand 11 (0 – 31) Unsure 1.3 (0.1 – 2.3) -2.2 (0.53 – -0.2)
Niger 22 (2 – 56) Unsure 1.6 (0.7 – 3.5) 41 (2.3 – -3.1)
Nigeria 107 (84 – 138) Increasing 1.4 (1.1 – 1.7) 11 (5.4 – -340)
North Macedonia 34 (17 – 49) Unsure 0.9 (0.6 – 1.3) -14 (13 – -4.7)
Norway 86 (68 – 123) Unsure 1 (0.8 – 1.2) -300 (13 – -12)
Oman 106 (79 – 204) Unsure 1.1 (0.8 – 1.6) 37 (7.2 – -14)
Pakistan 726 (646 – 821) Increasing 1.2 (1 – 1.4) 15 (9.4 – 34)
Palestine 27 (7 – 100) Unsure 2.2 (0.2 – 5.6) 29 (1.5 – -1.8)
Panama 174 (114 – 229) Unsure 1 (0.9 – 1.2) 180 (15 – -18)
Peru 1310 (1147 – 1498) Likely increasing 1.1 (1 – 1.2) 56 (22 – -100)
Philippines 190 (158 – 235) Unsure 1 (0.7 – 1.2) -110 (17 – -12)
Poland 323 (288 – 370) Likely decreasing 0.9 (0.8 – 1) -63 (39 – -18)
Portugal 484 (387 – 533) Likely decreasing 0.9 (0.9 – 1) -74 (52 – -20)
Puerto Rico 77 (29 – 128) Unsure 1.2 (0.7 – 1.6) 16 (4.7 – -11)
Qatar 665 (546 – 718) Increasing 1.2 (1.2 – 1.3) 16 (9.5 – 37)
Romania 365 (305 – 417) Unsure 1 (0.9 – 1.2) 220 (19 – -25)
Russia 5377 (4933 – 5678) Increasing 1.1 (1.1 – 1.3) 29 (21 – 53)
Saudi Arabia 1137 (1029 – 1287) Increasing 1.2 (1 – 1.3) 21 (13 – 54)
Senegal 46 (25 – 69) Increasing 1.5 (1.1 – 2) 7.1 (3.6 – 250)
Serbia 211 (157 – 260) Decreasing 0.8 (0.7 – 0.9) -12 (-38 – -7.2)
Singapore 1107 (1003 – 1240) Increasing 1.3 (1.1 – 1.4) 13 (9.4 – 22)
Slovakia 74 (35 – 181) Unsure 1.2 (0.7 – 1.7) 80 (5.8 – -7.1)
Somalia 59 (35 – 86) Increasing 1.5 (1.1 – 2) 7.2 (3.3 – -55)
South Africa 242 (161 – 300) Likely increasing 1.2 (0.9 – 1.5) 19 (8.9 – -140)
South Korea 46 (3 – 141) Unsure 1.6 (0.2 – 3.4) -4.8 (1.8 – -1.4)
Spain 4971 (4442 – 5239) Increasing 1.1 (1 – 1.1) 67 (30 – -330)
Sweden 694 (599 – 778) Likely increasing 1.1 (1 – 1.3) 31 (15 – -84)
Switzerland 189 (144 – 268) Decreasing 0.8 (0.7 – 0.8) -11 (-37 – -6.9)
Thailand 33 (14 – 53) Unsure 1.1 (0.2 – 1.6) -300 (3.9 – -4.2)
Tunisia 26 (4 – 78) Unsure 1 (0.2 – 2) -12 (4.6 – -2.3)
Turkey 3411 (3223 – 3603) Decreasing 0.9 (0.9 – 0.9) -29 (-50 – -21)
Ukraine 497 (429 – 637) Likely increasing 1.1 (1 – 1.3) 48 (15 – -35)
United Arab Emirates 484 (429 – 557) Increasing 1.1 (1 – 1.2) 22 (12 – 590)
United Kingdom 4758 (4551 – 4945) Decreasing 0.9 (0.9 – 1) -71 (360 – -37)
United Republic of Tanzania 54 (19 – 217) Likely increasing 1.6 (0.8 – 3.3) 9.9 (3.4 – -9.8)
United States of America 24684 (23807 – 25419) Decreasing 0.9 (0.9 – 0.9) -33 (-43 – -27)
Uruguay 30 (0 – 59) Unsure 1.6 (0.4 – 2.7) 14 (2.3 – Inf)
Uzbekistan 64 (30 – 135) Unsure 0.9 (0.4 – 1.5) -14 (13 – -4.3)